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Use pandas to Visualize Bing Ads Data in Python

The CData Python Connector for Bing Ads enables you use pandas and other modules to analyze and visualize live Bing Ads data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Bing Ads, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Bing Ads-connected Python applications and scripts for visualizing Bing Ads data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Bing Ads data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Bing Ads data in Python. When you issue complex SQL queries from Bing Ads, the driver pushes supported SQL operations, like filters and aggregations, directly to Bing Ads and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Bing Ads Data

Connecting to Bing Ads data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

The Bing Ads APIs use the OAuth 2 standard. To authenticate, you will need valid Bing Ads OAuth credentials and you will need to obtain a developer token. See the Getting Started section in the Bing Ads data provider help documentation for an authentication guide.

Follow the procedure below to install the required modules and start accessing Bing Ads through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Bing Ads Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Bing Ads data.

engine = create_engine("bingads:///? OAuthClientId=MyOAuthClientId& OAuthClientSecret=MyOAuthClientSecret& CallbackURL=http://localhost:portNumber& AccountId=442311& CustomerId=5521444& DeveloperToken=11112332233&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Bing Ads

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT Id, Name FROM AdGroups WHERE CampaignId = '234505536'", engine)

Visualize Bing Ads Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Bing Ads data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Id", y="Name")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the Bing Ads Python Connector to start building Python apps and scripts with connectivity to Bing Ads data. Reach out to our Support Team if you have any questions.



Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("bingads:///? OAuthClientId=MyOAuthClientId& OAuthClientSecret=MyOAuthClientSecret& CallbackURL=http://localhost:portNumber& AccountId=442311& CustomerId=5521444& DeveloperToken=11112332233&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, Name FROM AdGroups WHERE CampaignId = '234505536'", engine)

df.plot(kind="bar", x="Id", y="Name")
plt.show()